Daily Outfit
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About this skill
Problem
“Daily Outfit” addresses the moment-to-moment decision behind “what should I wear today?” A user may know the context, such as a 25°C workday or a first date, but still needs help turning existing clothes into a coherent look. The skill is designed for quick text-based outfit planning without weather APIs or photo uploads.
How It Works
It first captures the minimum useful context: occasion sets the style direction, weather affects layering, wardrobe items constrain the recommendations, and optional preferences shape the fit. It then returns at least two options, each with a one-line direction such as “polished minimal” or “relaxed casual,” followed by tops, bottoms, shoes, accessories, and practical cautions. If the user lists items like “white shirt, black trousers, grey hoodie” using color + type, the skill focuses on reusing what they already own, including multiple outfits from a small capsule wardrobe.
Boundaries
It is suitable for everyday styling advice for work, dates, interviews, travel, and casual wear. It does not provide brand recommendations, purchase links, garment design, pattern-making, or laundry/care instructions, and it should not be used to evaluate body image. Weather and wardrobe details must be supplied by the user; the output is a reference, not a fashion judgment.
Use Cases
- A user states a 25°C commute and existing tops/bottoms, then the skill drafts two work looks.
- A user lists 10 frequently worn items, and the skill builds seven distinct weekday pairings with accessories.
- Before an interview, a user states occasion, temperature, and style preference for two formal outfit plans.
- For a first date, a user asks what to wear, and the skill clarifies venue, style, and available items.
Best For
- Office workers who need quick commute outfit choices using only existing clothes
- People preparing for dates or interviews who want multiple style options without new purchases
- Individuals building a capsule wardrobe and pairing a small set of basics for a week
- Users seeking text-based styling advice instead of shopping links or care instructions
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